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Coding Interview AI Solver

Real-Time AI Coding Interview Solver & Algorithm Assistant

Cracking algorithmic interviews requires quick recall of data structures and edge cases. Kairo identifies pattern matches instantly.

Fit signals

Review the role before you tailor anything

A fit score is a triage aid, not a hiring prediction. Use it to decide what deserves a closer read.

Optical character recognition (OCR) for code snippets

Algorithmic pattern matching (DP, Two Pointers, Graph Traversal)

Time and space complexity (Big-O) breakdown

A practical search plan

Build a smaller, higher-signal pipeline

01

Screen Capture Code Prompt

Press a hotkey to capture the LeetCode or CoderPad problem.

02

Review Algorithm Strategy

Read Kairo's high-level strategy and edge cases before coding.

03

Implement & Explain

Synthesize the solution into clean code while explaining your trade-offs.

What Kairo automates

  • Searches a live jobs source using your role, location, and work-mode filters.
  • Ranks results against the career profile and documents you choose to provide.
  • Creates a role-specific CV draft from the job description when you request one.

What stays in your hands

  • You decide which roles are worth pursuing and which listings to dismiss.
  • You review every generated document before downloading or sending it.
  • You open the employer's source page and complete the application yourself.

Review before you apply

Generated suggestions are drafts. Accuracy, eligibility, and final application choices always need your judgment.

  1. 1Always explain code trade-offs out loud to the interviewer.
  2. 2Double check edge cases like empty arrays and null inputs.
  3. 3Avoid blindly typing generated code without understanding execution flow.

Questions about this workflow

Does Kairo support Python, Java, C++, and TypeScript?

Yes, Kairo supports all major programming languages including Python, C++, Java, Go, TypeScript, and Rust.

Can Kairo analyze time complexity?

Yes, every suggested approach includes a Big-O time and space complexity explanation.